CN114244658A - Channel estimation method based on multiple angle estimation in large-scale MIMO system - Google Patents

Channel estimation method based on multiple angle estimation in large-scale MIMO system Download PDF

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CN114244658A
CN114244658A CN202111599524.3A CN202111599524A CN114244658A CN 114244658 A CN114244658 A CN 114244658A CN 202111599524 A CN202111599524 A CN 202111599524A CN 114244658 A CN114244658 A CN 114244658A
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李紫薇
王海泉
俞芸芸
楼斌剑
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Hangzhou Dianzi University
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Abstract

The invention particularly relates to a channel estimation method based on multiple angle estimation in a large-scale MIMO system. The method comprises the steps that S1 a receiving terminal receives signals sent by a base station and obtains preliminary estimation channel information according to the received signals; s2, selecting part of preliminary estimation channel information and constructing a Hankel matrix; s3, performing singular value decomposition on the Hankel matrix, and obtaining a reconstruction matrix according to a singular value decomposition result; s4, obtaining a plurality of multiple angles according to the characteristic values in the reconstruction matrix, and obtaining a plurality of actual arrival angles through restoration based on the multiple angles; s5, respectively calculating to obtain multiple sets of azimuth arrival angle estimated values and channel complex gain coefficient estimated values according to each actual arrival angle; s6, selecting a group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values with the highest channel utilization rate; and S7, recovering the channel state information based on the selected azimuth arrival angle estimated value and the channel complex gain coefficient estimated value. The influence of too close angles in multipath on estimation is reduced, and the accuracy of channel estimation is improved.

Description

Channel estimation method based on multiple angle estimation in large-scale MIMO system
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a channel estimation method based on multiple angle estimation in a large-scale MIMO system.
Background
In a large-scale MIMO system, in order to accurately recover a transmission signal at a receiving end, various measures are taken to counteract the influence of multipath effects on a transmission signal. The realization of channel estimation needs to know the information of the wireless channel, and whether detailed channel information can be obtained, so that the transmitting signal can be correctly demodulated at the receiving end, which is an important index for measuring the performance of the wireless communication system. Therefore, channel estimation is a key technique for wireless communication systems. Meanwhile, accurate DOA estimation is crucial for the base station to perform downlink precoding/beamforming, that is, the system performance depends on how good the DOA estimation is, which is very necessary to develop a DOA estimation algorithm with high accuracy in a massive MIMO system.
For a large-scale MIMO system, the accuracy of estimation is improved on the premise of reducing pilot frequency as much as possible to obtain accurate channel information in real time, otherwise, the cost of training amount and feedback overhead is too high, and the real-time performance of communication is affected. In order to better improve the utilization efficiency of system resources, the DOA estimation method can be optimized to improve the accuracy of angle estimation to reduce the feedback overhead.
In view of the above technical problems, it is desirable to improve.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a channel estimation method based on multiple angle estimation in a large-scale MIMO system, so that the influence of too close angles in multipath on estimation is reduced, and the accuracy of channel estimation is further improved.
The invention adopts the following technical scheme:
the channel estimation method based on multiple angle estimation in the massive MIMO system comprises the following steps:
s1, the receiving end receives the signal sent by the base station and obtains preliminary estimation channel information according to the received signal;
s2, selecting part of preliminary estimation channel information and constructing a Hankel matrix;
s3, performing singular value decomposition on the Hankel matrix, and obtaining a reconstruction matrix according to a singular value decomposition result;
s4, obtaining a plurality of multiple angles according to the characteristic values in the reconstruction matrix, and obtaining a plurality of actual arrival angles through restoration based on the multiple angles;
s5, respectively calculating to obtain multiple sets of azimuth arrival angle estimated values and channel complex gain coefficient estimated values according to each actual arrival angle;
s6, selecting a group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values with the highest channel utilization rate;
and S7, recovering the channel state information based on the selected azimuth arrival angle estimated value and the channel complex gain coefficient estimated value.
As a preferred scheme, the calculation formula of the preliminary estimation channel information h is as follows:
Figure BDA0003432739440000021
wherein, P represents the number of propagation paths from the base station to the user; beta is alA channel complex gain coefficient representing the l path; alpha (theta)l) A channel steering vector representing the l-th path; thetalThe azimuth arrival angle of the ith path.
Preferably, the channel steering vector of the ith path is represented as:
Figure BDA0003432739440000031
wherein, λ represents the carrier wavelength, d is the distance between antenna elements, j represents the imaginary unit, T represents the transposition, and M represents the number of antennas equipped at the base station.
Preferably, in step S1, based on the expression of the channel steering vector, the preliminary estimated channel information is expressed as:
Figure BDA0003432739440000032
preferably, step S2 includes the steps of:
s2.1, selecting part of preliminary estimation channel information h1,h3,…,h2N-1N represents a positive integer;
s2.2, estimating channel information h according to part of preliminary estimation1,h3,…,h2N-1Constructing a Hankel matrix H:
Figure BDA0003432739440000033
Figure BDA0003432739440000034
Figure BDA0003432739440000035
expressed as a set of all complex matrices of size Q rows and L columns, satisfying the condition Q + L-1-N, Q ≧ P, L ≧ P.
Preferably, step S3 includes the steps of:
s3.1, performing singular value decomposition on the Hankel matrix H:
H＝UDVH
wherein U and V are unitary matrices of size QxL and LxL, respectively, D is a diagonal matrix, the superscript H denotes taking the conjugate transpose,
D＝diag(d1，d2，…，dL)
and d is1，d2，…，dLAre singular values, satisfy d1≥d2≥…≥dL≥0；
S3.2, taking the first Q-1 row and the first P column of the U as U1For U, take line 2 to line Q and the first P column as U2：
U1＝U1:Q-1,1:P
U2＝U2:Q,1:P
S3.3 according to U1、U2Calculating to obtain a reconstruction matrix H1The calculation formula is as follows:
H1＝(U1 HU1)-1U1 HU2。
preferably, step S4 includes:
s4.1, taking a reconstruction matrix H1Characteristic value λ ofiI-1, 2, …, P, in polar coordinate form
Figure BDA0003432739440000041
riThe magnitude of the amplitude is represented as,
Figure BDA0003432739440000042
as the actual angle of arrival
Figure BDA0003432739440000043
The double angle of (a), namely:
Figure BDA0003432739440000044
the following two cases are distinguished:
when in use
Figure BDA0003432739440000045
When the temperature of the water is higher than the set temperature,
Figure BDA0003432739440000046
or
Figure BDA0003432739440000047
When in use
Figure BDA0003432739440000048
When the temperature of the water is higher than the set temperature,
Figure BDA0003432739440000049
or
Figure BDA00034327394400000410
S4.2, byP double angles are reduced to obtain 2PAnd an actual angle of arrival.
Preferably, step S5 includes the steps of:
s5.1, mixing 2PSubstituting the actual arrival angle into the channel guide vector expression, and calculating to obtain 2PGroup azimuth arrival angle estimates;
s5.2, according to each group of azimuth arrival angle estimation values and the selected part of preliminary estimation channel information, calculating to obtain a channel complex gain coefficient estimation value corresponding to each group of azimuth arrival angle estimation values to form 2PAnd (4) forming an azimuth arrival angle estimation value and a channel complex gain coefficient estimation value.
Preferably, step S6 includes the steps of:
s6.1, calculating channel values of each group based on the estimated value of the azimuth arrival angle and the estimated value of the channel complex gain coefficient of each group respectively
Figure BDA0003432739440000051
F＝1,2，...，2P；
S6.2, according to the channel value
Figure BDA0003432739440000052
Calculating the selected part of preliminary estimation channel information h' to obtain the channel utilization rate of each group;
and S6.3, selecting a group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values with the highest channel utilization rate.
Preferably, in step S6.2, the calculation formula of the channel utilization rate is as follows:
Figure BDA0003432739440000053
the invention has the beneficial effects that:
the channel estimation method based on a small amount of unified training sequences reduces the influence of too close angles in multipath on estimation, realizes higher channel utilization rate, further improves the accuracy of channel estimation, and lays a foundation for further improving the system performance.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a channel estimation method based on multiple angle estimation in a massive MIMO system according to the present invention;
fig. 2 is a graph comparing channel utilization for different methods.
Detailed Description
The following description of the embodiments of the present invention is provided by way of specific examples, and other advantages and effects of the present invention will be readily apparent to those skilled in the art from the disclosure herein. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
The first embodiment is as follows:
the method of the present invention is illustrated by specific examples in this example, which improves upon the deficiencies of the DOA estimation method.
The specific application case is as follows:
assume that there are 1 user, 1 base station and the number of antennas of the base station is 128. Table 1 below gives the general parameter settings for channel estimation according to the parameters in table 1.
Figure BDA0003432739440000061
Figure BDA0003432739440000071
TABLE 1 parameter settings
Referring to fig. 1, the channel estimation method based on multiple angle estimation in a massive MIMO system includes the steps of:
s1, the receiving end receives the signal sent by the base station and obtains preliminary estimation channel information according to the received signal;
s2, selecting part of preliminary estimation channel information and constructing a Hankel matrix;
s3, performing singular value decomposition on the Hankel matrix, and obtaining a reconstruction matrix according to a singular value decomposition result;
s4, obtaining a plurality of multiple angles according to the characteristic values in the reconstruction matrix, and obtaining a plurality of actual arrival angles through restoration based on the multiple angles;
s5, respectively calculating to obtain multiple sets of azimuth arrival angle estimated values and channel complex gain coefficient estimated values according to each actual arrival angle;
s6, selecting a group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values with the highest channel utilization rate;
and S7, recovering the channel state information based on the selected azimuth arrival angle estimated value and the channel complex gain coefficient estimated value.
The channel estimation method based on a small amount of unified training sequences reduces the influence of too close angles in multipath on estimation, realizes higher channel utilization rate, further improves the accuracy of channel estimation, and lays a foundation for further improving the system performance.
Specifically, the method comprises the following steps:
suppose that the large-scale antenna system comprises 1 single-antenna user and 1 base station, and the base station is provided with 128 antennas. The step S1 is specifically that the user terminal records a channel obtained by the initial estimation of the received signal as h.
The base station antenna in the large-scale antenna system adopts a linear array arrangement mode, and channels from a base station to users are represented as follows:
Figure BDA0003432739440000081
wherein, betalA channel complex gain coefficient representing the l path; alpha (theta)l) A channel steering vector representing the l-th path; thetalThe azimuth arrival angle of the ith path.
Further, the channel steering vector of the ith path is represented as:
Figure BDA0003432739440000082
where λ represents the carrier wavelength, d is the distance between antenna elements, j represents the imaginary unit, and T represents the transposition.
Further, based on the expression of the channel steering vector, the preliminary estimation channel information in this embodiment can be expressed as:
Figure BDA0003432739440000083
further, step S2 includes the steps of:
s2.1, selecting part of preliminary estimation channel information h1,h3,…,h63；
S2.2, estimating channel information h according to part of preliminary estimation1,h3,…,h63Constructing a Hankel matrix H:
Figure BDA0003432739440000084
then
Figure BDA0003432739440000091
Matrix, and satisfies the condition Q + L-1-N-32.
Further, step S3 includes the steps of:
s3.1, performing Singular Value Decomposition (SVD) on the Hankel matrix H:
H＝UDVH
wherein the content of the first and second substances,
Figure BDA0003432739440000092
is a unitary matrix of which the number of bits is one,
Figure BDA0003432739440000093
is a unitary matrix of which the number of bits is one,
Figure BDA0003432739440000094
is a diagonal matrix, the superscript H represents taking the conjugate transpose,
D＝diag(d1，d2，…，d16)
and d is1，d2，…，d16Are singular values, satisfy d1≥d2≥…≥d16≥0；
S3.2, taking the first 16 rows and the first 4 columns of U as U1For U, take line 2 to line 17 and the first 4 columns as U2：
U1＝U1:16,1:4
U2＝U2:17,1:4
S3.3 according to U1、U2Calculating to obtain a reconstruction matrix H1The calculation formula is as follows:
H1＝(U1 HU1)-1U1 HU2。
further, step S4 includes:
s4.1, taking a reconstruction matrix H1Characteristic value λ ofiI is 1,2, …, 4 in polar coordinate form
Figure BDA0003432739440000095
riThe magnitude of the amplitude is represented as,
Figure BDA0003432739440000096
as the actual angle of arrival
Figure BDA0003432739440000097
Twice the angle of (i.e.：
Figure BDA0003432739440000098
It can be seen that the following two cases are distinguished:
when in use
Figure BDA0003432739440000099
When the temperature of the water is higher than the set temperature,
Figure BDA00034327394400000910
or
Figure BDA00034327394400000911
When in use
Figure BDA00034327394400000912
When the temperature of the water is higher than the set temperature,
Figure BDA00034327394400000913
or
Figure BDA00034327394400000914
S4.2, through 4 double angles, 16 actual arrival angles can be obtained through reduction.
Further, step S5 includes the steps of:
s5.1, sequentially substituting 16 actual arrival angles into a guiding vector expression alpha (theta)l) Reducing to respectively obtain 16 groups of position arrival angle estimated values which are recorded as
Figure BDA0003432739440000101
S5.2, estimating the angle of arrival according to each group of azimuth
Figure BDA0003432739440000102
And the selected part of the preliminary estimated channel information h1,h3,…,h63And obtaining channel complex increase corresponding to each group of azimuth arrival angle estimated values by utilizing least square estimation (LS) calculationCoefficient of benefit estimation
Figure BDA0003432739440000103
To form 16 sets of position angle-of-arrival estimation values and channel complex gain coefficient estimation values.
Further, step S6 includes the steps of:
s6.1, respectively calculating channel values of each group based on each group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values
Figure BDA0003432739440000104
Figure BDA0003432739440000104
1,2, 16, the calculation formula adopts
Figure BDA0003432739440000105
Channel value
Figure BDA0003432739440000106
Expressed as:
Figure BDA0003432739440000107
s6.2, according to the channel value
Figure BDA0003432739440000108
And calculating the selected part of the preliminary estimation channel information h' to obtain the channel utilization ratio of each group, wherein:
Figure BDA0003432739440000109
the calculation formula of the channel utilization rate is as follows:
Figure BDA0003432739440000111
s6.3, selecting a group of azimuth arrival angle estimated values with the highest channel utilization rate
Figure BDA0003432739440000112
Channel complex gain coefficient estimation
Figure BDA0003432739440000113
Further, in step S7, the estimated value of the angle of arrival is obtained according to the selected azimuth
Figure BDA0003432739440000114
By the formula
Figure BDA0003432739440000115
Channel steering vectors can be reconstructed
Figure BDA0003432739440000116
Finally, the reconstructed channel steering vector is used
Figure BDA0003432739440000117
And the selected channel complex gain coefficient estimation value
Figure BDA0003432739440000118
The recovered channel ensemble information is expressed as:
Figure BDA0003432739440000119
referring to fig. 2, the conventional channel method is based on the channel estimation of the prony-kung method, and the channel utilization rate of the prony-kung method is about 81.0% under the condition that the signal-to-noise ratio is 10 dB. The channel estimation method of the invention shows that the channel utilization rate is 91.3% in simulation under the condition of the same signal-to-noise ratio, and the channel utilization rate is increased along with the increase of the signal-to-noise ratio of the system. Obviously, compared with the traditional channel estimation method, the method provided by the embodiment of the invention has the advantage that the channel utilization rate is improved, so that the method has better system performance compared with the traditional method.
The above-mentioned embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention by those skilled in the art should fall within the protection scope of the present invention without departing from the design spirit of the present invention.

Claims (10)

1. The channel estimation method based on multiple angle estimation in the large-scale MIMO system is characterized by comprising the following steps:
s1, the receiving end receives the signal sent by the base station and obtains preliminary estimation channel information according to the received signal;
s2, selecting part of preliminary estimation channel information and constructing a Hankel matrix;
s3, performing singular value decomposition on the Hankel matrix, and obtaining a reconstruction matrix according to a singular value decomposition result;
s4, obtaining a plurality of multiple angles according to the characteristic values in the reconstruction matrix, and obtaining a plurality of actual arrival angles through restoration based on the multiple angles;
s5, respectively calculating to obtain multiple sets of azimuth arrival angle estimated values and channel complex gain coefficient estimated values according to each actual arrival angle;
s6, selecting a group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values with the highest channel utilization rate;
and S7, recovering the channel state information based on the selected azimuth arrival angle estimated value and the channel complex gain coefficient estimated value.
2. The method as claimed in claim 1, wherein the preliminary estimation channel information h is calculated by the following formula:
Figure FDA0003432739430000011
wherein, P represents the number of propagation paths from the base station to the user; beta is alA channel complex gain coefficient representing the l path; alpha (theta)l) To representChannel steering vector of the l path; thetalThe azimuth arrival angle of the ith path.
3. The method of claim 2, wherein the channel steering vector of the l-th path is expressed as:
Figure FDA0003432739430000021
wherein, λ represents the carrier wavelength, d is the distance between antenna elements, j represents the imaginary unit, T represents the transposition, and M represents the number of antennas equipped at the base station.
4. The method of claim 3, wherein in step S1, based on the expression of the channel steering vector, the preliminary estimation channel information is expressed as:
Figure FDA0003432739430000022
5. the method for channel estimation based on multiple angle estimation in massive MIMO system as claimed in claim 4, wherein the step S2 comprises the steps of:
s2.1, selecting part of preliminary estimation channel information h1,h3,…,h2N-1N represents a positive integer;
s2.2, estimating channel information h according to part of preliminary estimation1,h3,…,h2N-1Constructing a Hankel matrix H:
Figure FDA0003432739430000023
Figure FDA0003432739430000024
Figure FDA0003432739430000025
expressed as a set of all complex matrices of size Q rows and L columns, satisfying the condition Q + L-1-N, Q ≧ P, L ≧ P.
6. The method for channel estimation based on multiple angle estimation in massive MIMO system as claimed in claim 5, wherein the step S3 comprises the steps of:
s3.1, performing singular value decomposition on the Hankel matrix H:
H＝UDVH
wherein U and V are unitary matrices of size QxL and LxL, respectively, D is a diagonal matrix, the superscript H denotes taking the conjugate transpose,
D＝diag(d1，d2，…，dL)
and d is1，d2，…，dLAre singular values, satisfy d1≥d2≥…≥dL≥0；
S3.2, taking the first Q-1 row and the first P column of the U as U1For U, take line 2 to line Q and the first P column as U2：
U1＝U1:Q-1,1:P
U2＝U2:Q,1:P
S3.3 according to U1、U2Calculating to obtain a reconstruction matrix H1The calculation formula is as follows:
H1＝(U1 HU1)-1U1 HU2。
7. the method for channel estimation based on multiple angle estimation in massive MIMO system as claimed in claim 6, wherein the step S4 comprises:
s4.1, taking a reconstruction matrix H1Characteristic value λ ofi，i＝1,2，…，P，In polar coordinate form of
Figure FDA0003432739430000031
riThe magnitude of the amplitude is represented as,
Figure FDA0003432739430000032
as the actual angle of arrival
Figure FDA0003432739430000033
The double angle of (a), namely:
Figure FDA0003432739430000034
the following two cases are distinguished:
when in use
Figure FDA0003432739430000035
When the temperature of the water is higher than the set temperature,
Figure FDA0003432739430000036
or
Figure FDA0003432739430000037
When in use
Figure FDA0003432739430000038
When the temperature of the water is higher than the set temperature,
Figure FDA0003432739430000039
or
Figure FDA00034327394300000310
S4.2, obtaining 2 by P double-angle reductionPAnd an actual angle of arrival.
8. The method for channel estimation based on multiple angle estimation in massive MIMO system as claimed in claim 7, wherein the step S5 comprises the steps of:
s5.1, mixing 2PSubstituting the actual arrival angle into the channel guide vector expression, and calculating to obtain 2PGroup azimuth arrival angle estimates;
s5.2, according to each group of azimuth arrival angle estimation values and the selected part of preliminary estimation channel information, calculating to obtain a channel complex gain coefficient estimation value corresponding to each group of azimuth arrival angle estimation values to form 2PAnd (4) forming an azimuth arrival angle estimation value and a channel complex gain coefficient estimation value.
9. The method for estimating a channel in a massive MIMO system according to claim 8, wherein the step S6 comprises the steps of:
s6.1, calculating channel values of each group based on the estimated value of the azimuth arrival angle and the estimated value of the channel complex gain coefficient of each group respectively
Figure FDA0003432739430000041
F＝1,2，...，2P；
S6.2, according to the channel value
Figure FDA0003432739430000042
Calculating the selected part of preliminary estimation channel information h' to obtain the channel utilization rate of each group;
and S6.3, selecting a group of azimuth arrival angle estimation values and channel complex gain coefficient estimation values with the highest channel utilization rate.
10. The method of claim 9, wherein in step S6.2, the channel utilization is calculated by the following formula:
Figure FDA0003432739430000043
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CN114338303A (en) * 2021-12-24 2022-04-12 杭州电子科技大学 Channel estimation method and system based on multi-dimensional Hankel matrix in large-scale MIMO system
CN114338303B (en) * 2021-12-24 2024-02-13 杭州电子科技大学 Channel estimation method and system based on multidimensional Hankel matrix in large-scale MIMO system

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